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• This API performs 3D average pooling on the input tensor with the kernel size of $kD * kH * kW$ and the stride of $sD * sH * sW$. $k$ is the kernel size, indicating the size of the pooling window. $s$ is the stride, indicating the stride of the pooling operation.
• Formula: The relationship among the input($N,C,D_{in},H_{in},W_{in}$), out($N,C,D_{out},H_{out},W_{out}$), pooling stride ($stride$), and kernelSize ($kD,kH,kW$) is as follows:$$D_{out}=\lfloor \frac{D_{in}+2*padding[0]-kernelSize[0]}{stride[0]}+1 \rfloor$$ $$H_{out}=\lfloor \frac{H_{in}+2*padding[1]-kernelSize[1]}{stride[1]}+1 \rfloor$$ $$W_{out}=\lfloor \frac{W_{in}+2*padding[2]-kernelSize[2]}{stride[2]}+1 \rfloor$$ $$out(N_i,C_i,d,h,w)=\frac{1}{kD*kH*kW}\sum_{k=0}^{kD-1}\sum_{m=0}^{kH-1}\sum_{n=0}^{kW-1}input(N_i,C_i,stride[0]*d+k,stride[1]*h+m,stride[2]*w+n)$$

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Each operator has calls. First, aclnnAvgPool3dGetWorkspaceSize is called to obtain the workspace size required for computation and the executor that contains the operator computation process. Then, aclnnAvgPool3d is called to perform computation.

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• Parameters:

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  • For the [object Object]Atlas inference products[object Object], the data types of the self and out parameters do not support BFLOAT16.

• Returns:

  [object Object]: status code. For details, see .

  The first-phase API implements input parameter verification. The following errors may be thrown.

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• Parameters:

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• Returns:

  [object Object]: status code. For details, see .

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• Deterministic compute:
  • aclnnAvgPool3d defaults to a deterministic implementation.

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The following example is for reference only. For details, see .